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Record W2392392400

The Study of High Oleic Acid Rapeseed Disease Resistance Related Genes by Transcriptome and iTRAQ Analysis

2015· article· en· W2392392400 on OpenAlexaff
Zhang Zhen-qia

Bibliographic record

VenueActa Agriculturae Boreali-Sinica · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant pathogens and resistance mechanisms
Canadian institutionsMinistry of Agriculture
Fundersnot available
KeywordsTranscriptomeBiologyGeneRapeseedOleic acidPlant disease resistanceBiochemistryGeneticsGene expressionBotany
DOInot available

Abstract

fetched live from OpenAlex

There are obvious differences between high oleic acid rapeseed and low oleic acid rapeseed on sclerotinia sclerotiorum resistance. In order to find out the molecule mechanism,the high oleic acid rapeseed inbred line seeds 20-35 d after pollination were used as material for transcriptome analysis and i TRAQ analysis respectively in this study. The classifications associated with disease resistance were oxidative phosphorylation,plant hormone signal transduction and plant-pathogen interaction were discussed,and the relationship between differential genes and the corresponding protein were investigated too. Then real-time quantitative PCR( q PCR) analysis was used to verify the expression levels of differentially expressed genes which may be associated with disease resistance. Combined with previous study,the genes related with disease resistance were: gi | 260505503( polygalacturonase inhibitory protein),gi | 226346102( HSR203J-like protein) and gi | 470103214( caltractin-like). And the genes of gi | 297843222( binding protein),gi | 18397961( 2Fe-2S ferredoxin-like protein),gi | 196052306( NADH dehydrogenase subunit),gi |18423437( NADH dehydrogenase( ubiquinone) 1alpha subcomplex 5) and gi | 297794581( kinase family protein)have obvious difference.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.970
Threshold uncertainty score0.635

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.206
Teacher spread0.192 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueActa Agriculturae Boreali-SinicaSame topicPlant pathogens and resistance mechanismsFrench-language works237,207